Associate Principal Scientist Immunai, New York, United States
Introduction/Rationale: Despite advancements for Inflammatory Bowel Disease (IBD), high rates of non-response, relapse, and adverse effects underscore the need for novel therapeutic interventions. This necessity is compounded by the inherent complexity of IBD; wherein, multiple resident cellular components receive and generate aberrant signals within tissues and migrating immune cells.
Methods: To identify novel therapeutic targets, we constructed a harmonized single-cell tissue atlas (IBD atlas) derived from published clinical single-cell datasets. Machine learning-based methods were employed to extract relevant transcriptional signals and their contributing genes, which were then ranked using orthogonal translation metrics to generate a list of candidate targets for in vitro functional validation. Using this approach, we nominated candidates for cell type-specific functional evaluation in macrophages and fibroblasts. We utilized in vitro models optimized to recapitulate specific transcriptional states of these cells in inflamed IBD tissue, and evaluated the impact of target deletion in the presence or absence of appropriate ligands.
Results: We highlight a specific target for which deletion reduced the inflammatory proteome and induced an anti-inflammatory transcriptional state similar to that of healthy intestinal myeloid cells with a reduction in IBD associated signatures. Comparison to transcriptional shifts induced by standard-of-care therapies showed that this target's profile is distinct from anti-TNF and anti-integrin while recapitulating anti-inflammatory effects of JAK inhibitors. We contrast this with a second target for which ablation induced a proinflammatory response in macrophages but a favorable, anti-fibrotic response in intestinal fibroblasts highlighting two novel cell type targeted therapeutic approaches.
Conclusion: In conclusion, our framework leverages a robust single-cell data foundation to nominate disease-relevant targets in specific cell types optimally poised for desirable clinical outcomes.
